str(0.1 * args.num_procs * args.num_hours),
"num_hours_terminate":
str(0.9 * args.num_procs * args.num_hours)
})))
return mc
windows = fst.WindowExponential(
fst.args({
"alpha": "2.5",
"num": str(args.num_procs),
"maximum": str(args.max_particles)
})).boundaries()
print(windows)
if args.task == 0:
clones = fst.MakeClones()
for proc, win in enumerate(windows):
clones.add(mc(proc, win[0], win[1]))
clones.set(fst.MakeCheckpoint(fst.args({"file_name": "checkpoint.fst"})))
else:
clones = fst.MakeClones("checkpoint", args.num_procs)
#clones.initialize_and_run_until_complete()
clones.initialize_and_run_until_complete(
fst.args({
"ln_prob_file": "ln_prob.txt",
"omp_batch": str(int(1e6))
}))
print(clones.ln_prob().values())
open('clones.fst', 'w').write(clones.serialize())
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import feasst as fst
import pyfeasst
num_procs = 12
clones = fst.MakeClones('checkpoint', num_procs)
beta = clones.clone(0).thermo_params().beta()
volume = clones.clone(0).configuration().domain().volume()
plt.plot(clones.ln_prob().values(), label='T*=' + str(1. / beta))
sat = list()
for extrap_temp in np.arange(0.8, 1.201, 0.05):
extrap = fst.ExtrapolateBetaGCE(
clones,
fst.args({
"beta_new": str(1 / extrap_temp),
"beta_original": str(beta)
}))
extrap = pyfeasst.find_equilibrium(extrap, beta_mu_guess=-6)
plt.plot(extrap.ln_prob().values(),
label='T*=' + str(round(extrap_temp, 2)))
# tabulate saturation properties
num_vapor = extrap.average_macrostate(0)
num_liquid = extrap.average_macrostate(1)
sat.append([
extrap_temp, num_vapor / volume, num_liquid / volume,
extrap.betaPV() / volume * extrap_temp,
extrap.average(extrap.energy(), 0) / num_vapor,
extrap.average(extrap.energy(), 1) / num_liquid